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基于土耳其获得的兼容数据集,直接和间接方法得出的参考区间比较。

Comparison of reference intervals derived by direct and indirect methods based on compatible datasets obtained in Turkey.

机构信息

Department of Medical Biochemistry, Istanbul Health and Technology University School of Medicine, Istanbul, Turkey.

Faculty of Health Sciences, Yamaguchi University Graduate School of Medicine, Ube, Japan.

出版信息

Clin Chim Acta. 2021 Sep;520:186-195. doi: 10.1016/j.cca.2021.05.030. Epub 2021 Jun 1.

Abstract

BACKGROUND

Indirect derivation of reference intervals (RIs) from the laboratory information system (LIS) has been recently pursued. We aimed at evaluating the accuracy of indirectly predicted RIs compared to the RIs established directly from healthy subjects in the nationwide RI study in Turkey, targeting 25 major chemistry analytes.

METHODS

LIS data were retrieved from the laboratory that performed measurements for the direct study. They were cleaned by limiting to outpatients with age 18-65 years, and by allowing only one record per year per patient. Evaluated were four indirect methods of univariate approach: Hoffmann, Bhattacharya, Arzideh, and Wosniok methods. Power transformation of the LIS dataset was performed either using the power (λ) reported by the IFCC global RI study (the first two methods) or using a λ predicted (the last two).

RESULTS

Compared to the direct study dataset, the LIS dataset showed a variable degree of alterations in peak location and shape. Consequently, lower-side peak-shifts observed in sodium, albumin, etc. led to lowered RI limits, whereas higher-side peak-shift observed in triglyceride, low-density lipoprotein cholesterol, etc. led to raised RI limits. Overall, 72% (62-81) of the RI limits predicted by indirect methods showed significant biases from direct RIs. However, the biases observed in total cholesterol, lactic dehydrogenase, etc. were attributed to a higher-side age-bias in LIS dataset. After excluding them, the overall proportion of biased RIs was reduced to 47% (38-54).

CONCLUSION

To reduce prediction biases that remained after age adjustment, it is necessary to apply more rigorous data-cleaning before applying indirect methods.

摘要

背景

最近已经从实验室信息系统(LIS)间接推导参考区间(RI)。我们旨在评估与土耳其全国 RI 研究中直接从健康受试者建立的 RI 相比,间接预测 RI 的准确性,该研究针对 25 种主要化学分析物。

方法

从进行直接研究的实验室中检索 LIS 数据。通过将年龄在 18-65 岁的门诊患者限制在 1 年内每个患者仅允许 1 个记录,对四个单变量间接方法进行了评估:Hoffmann、Bhattacharya、Arzideh 和 Wosniok 方法。对 LIS 数据集进行幂变换,要么使用 IFCC 全球 RI 研究报告的幂(λ)(前两种方法),要么使用预测的 λ(后两种方法)。

结果

与直接研究数据集相比,LIS 数据集的峰位置和形状发生了不同程度的改变。因此,在钠、白蛋白等中观察到的较低侧峰移导致 RI 限制降低,而在甘油三酯、低密度脂蛋白胆固醇等中观察到的较高侧峰移导致 RI 限制升高。总体而言,72%(62-81)的间接方法预测的 RI 限制与直接 RI 存在显著偏差。然而,在总胆固醇、乳酸脱氢酶等中观察到的偏差归因于 LIS 数据集的较高侧年龄偏差。排除这些偏差后,偏倚 RI 的总体比例降至 47%(38-54)。

结论

为了减少年龄调整后仍然存在的预测偏差,在应用间接方法之前,有必要在应用间接方法之前进行更严格的数据清理。

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